Workflow Templates

AI Research Assistant via Telegram (GPT-4o mini + DeepSeek R1 + SerpAPI) 👥 Who’s it for This workflow is perfect for anyone who wants to receive AI-powered research summaries directly on Telegram. Ideal for people asking frequent product, tech, or decision-making questions and want up-to-date answers sourced from the web. 🤖 What it does Users send a question via Telegram. An AI agent (DeepSeek R1) reformulates and understands the intent, while a second agent (GPT-4o mini) performs live research using SerpAPI. The most relevant answers, including links and images, are delivered back via Telegram. ⚙️ How it works 📲 Telegram Trigger – Starts when a user sends a message to your Telegram bot. 🧠 DeepSeek R1 Agent – Understands, clarifies, or reformulates the user query. 🧠 Research AI Agent (GPT-4o mini + SerpAPI) – Searches the web and summarizes the best results. 📤 Send Telegram Message – Sends the response back to the same user. 📋 Requirements Telegram bot (via BotFather) with API token set in n8n credentials OpenAI account with API key and balance for GPT-4o mini SerpAPI account (100 free searches/month) with API key DeepSeek account with API key and balance 🛠️ How to set up Create your Telegram bot using BotFather and connect it using the Telegram Trigger node Set up DeepSeek credentials and add a Chat Model AI Agent node using DeepSeek R1 to reformulate the user’s question Set up OpenAI credentials and add a second ChatGPT AI Agent node using GPT-4o mini In the GPT-4o node, enable the SerpAPI Tool and add your SerpAPI API key Pass the reformulated question from DeepSeek to the GPT-4o agent for live search and summarization Format the response (text, links, optional images) Send the final reply to the user using the Telegram Send Message node Ensure your n8n instance is publicly accessible Test the workflow by sending a message to your Telegram bot ✅

Use Case Turn any web page into a compelling LinkedIn post — complete with an AI-generated image. This automation is ideal for sharing content like blog posts, case studies, or product updates in a polished and engaging format. What This Automation Does Given a page URL and optional user instructions, this automation: Scrapes the content of the webpage Uses AI to write a clear, educational, and LinkedIn-optimized post Sends both to Slack for review and approval Handles feedback and revisions via Slack interactions Input: Page URL** — The link to the webpage (required) Instructions** — Optional notes on tone, emphasis, or format Output: LinkedIn post text Slack message with review/approval options How It Works Form Submission: User inputs a web page and optional instructions. Web Scraping: Uses Airtop to extract page content. Post Generation: AI agent writes a post based on the page and instructions. Slack Review Flow: Post and image sent to Slack for feedback User can approve, request revisions, or decline Revisions trigger reprocessing steps automatically Final Post Delivery: Approved post is sent back to Slack, ready to publish. Setup Requirements Generate an Airtop API key completely free. Configure your OpenAI credentials for post and image prompt generation Slack OAuth credentials and a Slack channel Next Steps Post Directly**: Add LinkedIn publishing to automate the full content workflow. Template Variations**: Offer post style presets (e.g., technical, story-driven, short-form). CRM Sync**: Save approved posts and stats in Airtable or Notion for team use. Read more about generating social content using AI

Who this is for? Google SERP Tracker + Trends and Recommendations is an AI-powered n8n workflow that extracts Google search results via Bright Data, parses them into structured JSON using Google Gemini, and generates actionable recommendations and search trends. It outputs CSV reports and sends real-time Webhook notifications. This workflow is ideal for: SEO Agencies needing automated rank & trend tracking Growth Marketers seeking daily/weekly search-based insights Product Teams monitoring brand or competitor visibility Market Researchers performing search behavior analysis No-code Builders automating search intelligence workflows What problem is this workflow solving? Traditional tracking of search engine rankings and search trends is often fragmented and manual. Analyzing SERP changes and trends requires: Manual extraction or using unstable scrapers Unstructured or cluttered HTML data Lack of actionable insights or recommendations This workflow solves the problem by: Automating real-time Google SERP data extraction using Bright Data Structuring unstructured search data using Google Gemini LLM Generating actionable recommendations and trends Exporting both CSV reports automatically to disk for downstream use Notifying external systems via Webhook What this workflow does Accepts search input, zone name, and webhook notification URL Uses Bright Data to extract Google Search Results Uses Google Gemini LLM to parse the SERP data into structured JSON Loops over structured results to: Extract recommendations Extract trends Saves both as .csv files (example below): Google_SERP_Recommendations_Response_2025-06-10T23-01-50-650Z.csv Google_SERP_Trends_Response_2025-06-10T23-01-38-915Z.csv Sends a Webhook with the summary or file reference LLM Usage Google Gemini LLM handles: Parsing Google Search HTML into structured JSON Summarizing recommendation data Deriving trends from the extracted SERP metadata Setup Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication). The Value field should be set with the Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token. A Google Gemini API key (or access through Vertex AI or proxy). Update the Set input fields with the search criteria, Bright Data Zone name, Webhook notification URL. How to customize this workflow to your needs Input Customization Set your target keyword/phrase in the search field Add your webhook_notification_url for external triggers or notifications SERP Source You can extend the Bright Data search logic to include other engines like Bing or DuckDuckGo. Output Format Edit the .csv structure in the Convert to File nodes if you want to include/exclude specific columns. LLM Prompt Tuning The Gemini LLM prompt inside the Recommendation or Trends extractor nodes can be fine-tuned for domain-specific insight (e.g., SEO vs eCommerce focus).

Use case This workflow automatically qualifies great leads from a form and sends them an email 😮.. It also adds the user to Hubspot if not already added and records the outreach. How to setup Add you MadKudu, Hunter, and Gmail credentials Setup your HubSpot Oauth2 creds using n8n docs Set the email content and subject Click the Test Workflow button, enter your email and check the Slack channel Activate the workflow and use the form trigger production URL to collect your leads in a smart way How to adjust this template You may want to raise or lower the threshold for your leads, as you see fit. You also need to update the content (the email and the subject), obviously 😅.

🚀 AI-Powered YouTube Video Summary Distributor: From Channel to Community! Workflow Overview This sophisticated n8n automation transforms YouTube content discovery into a seamless, multi-platform intelligence sharing process. By intelligently connecting YouTube RSS, AI summarization, and content distribution platforms, the workflow: Discovers New Content: Monitors YouTube channels via RSS feed Captures latest video uploads Tracks content in real-time AI-Powered Summarization: Extracts video metadata Generates concise, meaningful summaries Leverages GPT-4o for intelligent content analysis Intelligent Distribution: Logs summaries in Google Sheets Sends summaries to Slack for review Publishes approved content to Reddit Detailed Setup Instructions 1. YouTube Data API Configuration Prerequisites Google Cloud Console account Enabled YouTube Data API v3 Setup Steps: Go to Google Cloud Console Create a new project Enable YouTube Data API v3 Create credentials (API Key) Store API key securely in n8n credentials Obtain channel RSS feed URL 2. OpenAI API Setup Prerequisites OpenAI account Active API subscription Configuration: Visit OpenAI Platform Generate API key Select GPT-4o model Configure API key in n8n credentials Set up billing and usage limits 3. Slack Integration Prerequisites Slack workspace Slack app permissions Setup Process: Create a Slack app in your workspace Configure OAuth scopes for sending messages Install app to workspace Obtain webhook or OAuth token Configure in n8n Slack node 4. Reddit API Configuration Prerequisites Reddit account Reddit application created Steps: Go to Reddit's app preferences Create a new application Obtain client ID and secret Configure OAuth2 credentials in n8n Select target subreddit Workflow Customization Channel Modification Replace YouTube RSS feed URL in trigger node Adjust channel_id parameter Modify extraction logic if needed Subreddit Customization Change subreddit parameter in Reddit node Adjust title and text formatting AI Summarization Tuning Modify system message in Summarizer Agent Adjust prompt for different content types Implement custom filtering Key Customization Points Modify RSS feed URL Change target subreddit Adjust AI summarization prompt Add custom filtering logic Implement multi-channel support Technical Requirements n8n v0.220.0 or higher YouTube Data API v3 OpenAI API access Slack workspace Reddit application Stable internet connection Potential Use Cases Content creator content tracking Research and trend analysis Social media content distribution Automated content curation Community engagement Security Considerations Use environment variables for API keys Implement proper OAuth2 authentication Respect platform usage guidelines Maintain user privacy Future Enhancement Roadmap Multi-language support Advanced content filtering Sentiment analysis integration Expanded platform distribution Customizable summarization parameters Workflow Visualization [YouTube RSS Trigger] ⬇️ [Extract Channel ID] ⬇️ [Fetch Video Details] ⬇️ [AI Summarization] ⬇️ [Google Sheets Logging] ⬇️ [Slack Approval] ⬇️ [Reddit Publishing] Hashtag Performance Boost 🚀 #YouTubeAutomation #AIContentDistribution #WorkflowInnovation #ContentCuration #AIMarketing #DigitalMediaTech #AutomatedSummaries #CrossPlatformContent Connect With Me Ready to revolutionize your content workflow? 📧 Email: Yaron@nofluff.online 🎥 YouTube: @YaronBeen 💼 LinkedIn: Yaron Been Transform your content strategy with intelligent, automated workflows! Note: Always test and customize the workflow to fit your specific use case and comply with platform guidelines.

Automated outreach system that identifies and contacts potential leads from CrunchBase with personalized, timely messages. 🚀 What It Does Identifies target companies and contacts Personalizes email content Schedules follow-ups Tracks responses Integrates with email providers 🎯 Perfect For Sales development reps Business development teams Startup founders Investment professionals Partnership managers ⚙️ Key Benefits ✅ Automated lead generation ✅ Personalized outreach at scale ✅ Follow-up automation ✅ Response tracking ✅ Time-saving workflow 🔧 What You Need CrunchBase API access Email service (e.g., Gmail, SendGrid) n8n instance CRM (optional) 📊 Features Contact information extraction Email template personalization Send time optimization Open/click tracking Response handling 🛠️ Setup & Support Quick Setup Start sending in 30 minutes with our step-by-step guide 📺 Watch Tutorial 💼 Get Expert Support 📧 Direct Help Transform your outbound sales process with automated, personalized outreach to high-quality leads from CrunchBase.

Who is this for? This workflow is designed for Customer Satisfaction Managers (CSM), sales professionals, and operations managers who need to automate the analysis of client transcripts, save summarized notes to HubSpot, and route relevant feedback to the appropriate departments via email. What problem is this workflow solving? / Use Case Manually processing client conversations, extracting key insights, and distributing them to the right teams is time-consuming and error-prone. This workflow automates: Transcript analysis** using AI (OpenAI) to identify relevant content. HubSpot integration** to log meeting notes against client records. Email routing** to ensure feedback reaches the correct departments (e.g., support, sales, product, admin). What this workflow does Input Transcript: Accepts a client conversation transcript (e.g., from emails, calls, or chats). HubSpot Sync: Searches for the client’s HubSpot ID using their email. Uploads a summarized version of the conversation as meeting notes. AI-Powered Routing: Uses an OpenAI model to analyze the transcript and categorize content by department. Triggers emails (via Gmail) to route feedback to the relevant teams. Form Completion: Ends the workflow with optional user confirmation. Setup Prerequisites: n8n instance (cloud or self-hosted). HubSpot API credentials (for contact lookup and notes upload). OpenAI API key (for transcript analysis). Gmail account (for sending emails). Configuration: Replace placeholder nodes (e.g., HubSpot, OpenAI, Gmail) with your authenticated accounts. Define email templates and recipient addresses for routing. Adjust the OpenAI prompt to match your categorization criteria (e.g., "support," "billing"). How to customize this workflow to your needs Transcript Sources**: Extend the workflow to pull transcripts from other sources (e.g., Zoom, Slack). Departments**: Modify the routing logic to include additional teams or conditions. Notifications**: Add Slack/MS Teams alerts for urgent feedback. Error Handling**: Introduce retries or fallback actions for failed HubSpot/Gmail steps.

This template is based on the following template. Thank you for the groundwork, Matheus. How it works: Store your snippets of text in a Notion table. Each snippet should have an image associated with it (copy + pasted into the text) Connect to your table via a Notion "integration", from which N8N can then query your pre-meditated posts The text is fed through an OpenAI assistant to boost engagement via formatting The re-formatted text along with the image pulled from the Notion snippet are combined into a post for your LinkedIn The row in the original Notion table from step 1 containing this post is set to a status of "Done" Set up steps: You will need to create a Notion "integration", which will yield a "secret key" which you enter into your N8N as a "Credential". You will need to create a LinkedIn "app" in order to post on your behalf. When creating your LinkedIn "app", you will be required to link this "app" to a company page on LinkedIn. If you are doing this for yourself, seach for the "Default Company Payge (for API testing)", and select this page as it is provided by LinkedIn for individuals. You can find your LinkedIn apps here, and if you get stuck, further instructions on setting up this workflow (including this LinkedIn OAuth piece) can be found in this YouTube Video Aide to these instructions. Lastly, you will need to create an OpenAI API key, found on your OpenAI Playground Dashboard. Once you created an API key, make sure you have an assistant created from the "Assistants" tab on the OpenAI dashboard. This assistant and its instructions will be needed for carrying out the re-formatting of your post.

This n8n template demonstrates how to use AI to score the all Resumes by matching it with Job profile Problem Statement: A Hr person is flooded with resume and spends hours manually checking each to find most suitable ones. How it works It is linked to Gmail Trigger which upon receving any mail with specific subject will check for the attachment. Attachment will be parsed to understand the resume Candidate informtion will be broken into Personal, Eductional and Professional type Job profile will be pulled from Notion Board A HR expert powered by Gemini LLM will score each profile on basis on its relevancy Information will be updated back to Gsheet Message lable will be updated back for clarity How to use The gmail trigger node is used as an example but feel free to replace this with other triggers such as webhook or even a form. Requirements Gemini account for LLM Google sheet for upload Gmail as trigger Llama parse credentials

How it works Automates the retrieval of Calvin and Hobbes daily comics. Extracts the comic image URL from the website. Translates comic dialogues to English and Korean. Posts the comic and translations to Discord daily. Set up steps Estimated setup time: ~10-15 minutes. Use a Schedule Trigger to automate the workflow at 9 AM daily. Add nodes for parameter setup, HTTP request, data extraction, and integration with Discord. Add detailed notes to each node in the workflow for easy understanding.

This workflow demonstrates a simple way to run evals on a set of test cases stored in a Google Sheet. The example we are using comes from an info extraction task dataset, where we tested 6 different LLMs on 18 different test cases. This workflow extends the functionality of my simple eval for benchmarking legal tasks here. Rather than running executions sequentially (waiting for each one to respond before making another request), we use parallel processing to fire 2 requests every second. You can see our sample data in this spreadsheet here to get started. Once you have this working for our dataset, you can plug in your own test cases matching different LLMs to see how it works with your own data. How it works Pull our test cases from Google Sheets. For each case, fire off an HTTP request to a webhook. That webhook grabs the relevant source file from Google Drive and converts it to text. The text gets sent to an LLM via Open Router (so we can easily swap out models). Results come back and are logged in Google Sheets. Set up steps: Add your credentials for Google Sheets, Google Drive, and OpenRouter. Make a copy of the original data spreadsheet so that you can edit it yourself. You will need to plug your version in the Update Results node to see the spreadsheet update on each run of the loop.

This template shows how to use the Question and Answer tool to save costs in RAG use cases. Who is this for? This template is for everyone who wants to start giving knowledge to their Agents through RAG. Requirements Have a PDF with custom knowledge that you want to provide to your agent. Setup No setup required. Just hit Execute Workflow, upload your knowledge document and then start chatting. How to customize this to your needs Add custom instructions to your Agent by changing the prompts in it. Add a different way to load in knowledge to your vector store, e.g. by looking at some Google Drive files or loading knowledge from a table. Describe your data properly in the Q&A tool Exchange the Simple Vector Store nodes with your own vector store tools ready for production. Add a more sophisticated way to rank files found in the vector store. For more information read our docs on RAG in n8n.